Improved Stereo Matching with Constant Highway Networks and Reflective Confidence Learning
相关工作 reflective loss层来检测网络CNN网络性能优劣 新网络来代替WTA 1.新网络结构， 多层多尺度控制网络的接受域 2.通过hybrid loss来训练网络获得更好的网络结构性能 3.通过CNN得到视差图而不是先前的WTA， 4.通过reflective来测量CNN输出准确性 5.如何利用confidence score更好的检测异常点并且进行修正 6.性能和速度有了很大的进
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相关文章
- 1. Improved Stereo Matching with Constant Highway Networks and Reflective Confidence Learning
- 2. Self-Supervised Learning for Stereo Matching with Self-Improving Ability
- 3. Unsupervised Learning of Stereo Matching
- 4. Confidence Inference for Focused Learning in Stereo Matching 论文笔记
- 5. FixMatch Simplifying Semi-Supervised Learning with Consistency and Confidence
- 6. Highway Networks VS Deep Residual Learning
- 7. Highway Networks
- 8. Pyramid Stereo Matching Network
- 9. 《Efficient Deep Learning for Stereo Matching》学习笔记
- 10. Universally Slimmable Networks and Improved Training Techniques_ICCV_2019